AB Test Setup
v1.0.0Plan A/B tests with a clear hypothesis, defined metrics, variant design, sample size, duration, and statistical significance guidelines.
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安全扫描
OpenClaw
安全
high confidenceThis is an instruction-only skill that provides a coherent, self-contained checklist and output template for planning A/B tests and does not request extra permissions, credentials, or perform any installs.
评估建议
This skill is an offline planning template for A/B tests and appears self-contained. You can install it safely from an access/permission perspective, but remember: (1) provide accurate traffic and baseline numbers when using the template so sample-size estimates are meaningful; (2) avoid including any personally identifiable information (PII) in examples you pass to the agent; and (3) the agent can invoke the skill autonomously by default — if you prefer manual control, disable autonomous invoca...详细分析 ▾
✓ 用途与能力
The name and description (A/B test planning) match the SKILL.md: it provides hypothesis, metrics, sample size, duration, design, and decision rules. The skill does not request unrelated binaries, env vars, or credentials.
✓ 指令范围
Runtime instructions are limited to planning steps, output formatting, and rules for running/deciding on tests. They do not instruct the agent to read local files, access environment variables, call external endpoints, or perform system operations.
✓ 安装机制
No install spec and no code files — the skill is instruction-only, so nothing is written to disk or installed during setup.
✓ 凭证需求
The skill declares no environment variables, credentials, or config paths and the instructions do not reference any secrets or external service tokens.
✓ 持久化与权限
always is false (no forced inclusion). disable-model-invocation is default false (agent may call the skill autonomously), which is normal for skills and acceptable here since the skill has no sensitive access.
安全有层次,运行前请审查代码。
运行时依赖
无特殊依赖
版本
latestv1.0.02026/3/22
Initial release
● Pending
安装命令 点击复制
官方npx clawhub@latest install sw-ab-test-setup
镜像加速npx clawhub@latest install sw-ab-test-setup --registry https://cn.clawhub-mirror.com
技能文档
Trigger
Plan A/B tests with proper methodology — hypothesis, sample size, duration, variant design, statistical significance.Trigger phrases: "A/B test", "split test", "experiment", "test this change", "variant", "multivariate test", "hypothesis"
Process
- Hypothesis: What are you testing and why?
- Metrics: Primary metric, guardrail metrics, success criteria
- Design: Control vs variant(s), what exactly changes
- Calculate: Sample size, test duration, minimum detectable effect
- Plan: Implementation, QA, analysis timeline
Output Format
# A/B Test Plan: [Name]Hypothesis
If we [change], then [metric] will [improve/increase] because [reason].Variants
- Control (A): [current experience]
- Variant (B): [proposed change — be specific]
Metrics
- Primary: [metric] — current: [X%] — target: [Y%]
- Guardrail: [metric that should NOT decrease]
Sample Size & Duration
- MDE: [minimum detectable effect, e.g., 10% relative]
- Sample needed: [N per variant]
- Current traffic: [X visitors/day to test area]
- Estimated duration: [Y days/weeks]
- Confidence level: 95%
Implementation Notes
[What needs to change, where, any technical considerations]Decision Framework
- If primary metric improves ≥ MDE with p < 0.05 → ship variant
- If no significant difference after [duration] → keep control
- If guardrail metric drops > [threshold] → stop test immediately
Rules
- Never run a test without a hypothesis
- One change per test (unless multivariate with sufficient traffic)
- Run for minimum 2 full business cycles (usually 2 weeks)
- Don't peek at results daily — pre-commit to evaluation date
- 95% confidence minimum. 80% power minimum.
- Document everything: future you needs to know why this was tested
数据来源:ClawHub ↗ · 中文优化:龙虾技能库
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